13 datasets found
  1. COVID-19 cases and deaths per million in 210 countries as of July 13, 2022

    • statista.com
    Updated Jul 13, 2022
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    Statista (2022). COVID-19 cases and deaths per million in 210 countries as of July 13, 2022 [Dataset]. https://www.statista.com/statistics/1104709/coronavirus-deaths-worldwide-per-million-inhabitants/
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    Dataset updated
    Jul 13, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

    The difficulties of death figures

    This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

    Where are these numbers coming from?

    The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

  2. COVID-19 Worldwide Daily Data

    • kaggle.com
    zip
    Updated Aug 28, 2020
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    Altadata (2020). COVID-19 Worldwide Daily Data [Dataset]. https://www.kaggle.com/altadata/covid19
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    zip(469881 bytes)Available download formats
    Dataset updated
    Aug 28, 2020
    Authors
    Altadata
    Description

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F5505749%2F2b83271d61e47e2523e10dc9c28e545c%2F600x200.jpg?generation=1599042483103679&alt=media" alt="">

    ALTADATA is a curated data marketplace where our subscribers and our data partners can easily exchange ready-to-analyze datasets and create insights with EPO, our visual data analytics platform.

    COVID-19 Worldwide Daily Data

    Daily global COVID-19 data for all countries, provided by Johns Hopkins University (JHU) Center for Systems Science and Engineering (CSSE). If you want to use the update version of the data, you can use our daily updated data with the help of api key by entering it via Altadata.

    Overview

    In this data product, you may find the latest and historical global daily data on the COVID-19 pandemic for all countries.

    The COVID‑19 pandemic, also known as the coronavirus pandemic, is an ongoing global pandemic of coronavirus disease 2019 (COVID‑19), caused by severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2). The outbreak was first identified in December 2019 in Wuhan, China. The World Health Organization declared the outbreak a Public Health Emergency of International Concern on 30 January 2020 and a pandemic on 11 March. As of 12 August 2020, more than 20.2 million cases of COVID‑19 have been reported in more than 188 countries and territories, resulting in more than 741,000 deaths; more than 12.5 million people have recovered.

    The Johns Hopkins Coronavirus Resource Center is a continuously updated source of COVID-19 data and expert guidance. They aggregate and analyze the best data available on COVID-19 - including cases, as well as testing, contact tracing and vaccine efforts - to help the public, policymakers and healthcare professionals worldwide respond to the pandemic.

    Methodology

    • Cases and Death counts include confirmed and probable (where reported)
    • Recovered cases are estimates based on local media reports, and state and local reporting when available, and therefore may be substantially lower than the true number. US state-level recovered cases are from COVID Tracking Project.
    • Active cases = total cases - total recovered - total deaths
    • Incidence Rate = cases per 100,000 persons
    • Case-Fatality Ratio (%) = Number recorded deaths / Number cases
    • Country Population represents 2019 projections by UN Population Division, integrated to the JHU CSSE's COVID-19 data by ALTADATA

    Data Source

    Related Data Products

    Suggested Blog Posts

    Data Dictionary

    • Reported Date (reported_date) : Covid-19 Report Date
    • Country_Region (country_region) : Country, region or sovereignty name
    • Population (population) : Country populations as per United Nations Population Division
    • Confirmed Case (confirmed) : Confirmed cases include presumptive positive cases and probable cases
    • Active cases (active) : Active cases = total confirmed - total recovered - total deaths
    • Deaths (deaths) : Death cases counts
    • Recovered (recovered) : Recovered cases counts
    • Mortality Rate (mortality_rate) : Number of recorded deaths * 100 / Number of confirmed cases
    • Incident Rate (incident_rate) : Confirmed cases per 100,000 persons
  3. COVID-19 Trends in Each Country

    • coronavirus-disasterresponse.hub.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +2more
    Updated Mar 28, 2020
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    Urban Observatory by Esri (2020). COVID-19 Trends in Each Country [Dataset]. https://coronavirus-disasterresponse.hub.arcgis.com/maps/a16bb8b137ba4d8bbe645301b80e5740
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    Dataset updated
    Mar 28, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    Earth
    Description

    On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit: World Health Organization (WHO)For more information, visit the Johns Hopkins Coronavirus Resource Center.COVID-19 Trends MethodologyOur goal is to analyze and present daily updates in the form of recent trends within countries, states, or counties during the COVID-19 global pandemic. The data we are analyzing is taken directly from the Johns Hopkins University Coronavirus COVID-19 Global Cases Dashboard, though we expect to be one day behind the dashboard’s live feeds to allow for quality assurance of the data.DOI: https://doi.org/10.6084/m9.figshare.125529863/7/2022 - Adjusted the rate of active cases calculation in the U.S. to reflect the rates of serious and severe cases due nearly completely dominant Omicron variant.6/24/2020 - Expanded Case Rates discussion to include fix on 6/23 for calculating active cases.6/22/2020 - Added Executive Summary and Subsequent Outbreaks sectionsRevisions on 6/10/2020 based on updated CDC reporting. This affects the estimate of active cases by revising the average duration of cases with hospital stays downward from 30 days to 25 days. The result shifted 76 U.S. counties out of Epidemic to Spreading trend and no change for national level trends.Methodology update on 6/2/2020: This sets the length of the tail of new cases to 6 to a maximum of 14 days, rather than 21 days as determined by the last 1/3 of cases. This was done to align trends and criteria for them with U.S. CDC guidance. The impact is areas transition into Controlled trend sooner for not bearing the burden of new case 15-21 days earlier.Correction on 6/1/2020Discussion of our assertion of an abundance of caution in assigning trends in rural counties added 5/7/2020. Revisions added on 4/30/2020 are highlighted.Revisions added on 4/23/2020 are highlighted.Executive SummaryCOVID-19 Trends is a methodology for characterizing the current trend for places during the COVID-19 global pandemic. Each day we assign one of five trends: Emergent, Spreading, Epidemic, Controlled, or End Stage to geographic areas to geographic areas based on the number of new cases, the number of active cases, the total population, and an algorithm (described below) that contextualize the most recent fourteen days with the overall COVID-19 case history. Currently we analyze the countries of the world and the U.S. Counties. The purpose is to give policymakers, citizens, and analysts a fact-based data driven sense for the direction each place is currently going. When a place has the initial cases, they are assigned Emergent, and if that place controls the rate of new cases, they can move directly to Controlled, and even to End Stage in a short time. However, if the reporting or measures to curtail spread are not adequate and significant numbers of new cases continue, they are assigned to Spreading, and in cases where the spread is clearly uncontrolled, Epidemic trend.We analyze the data reported by Johns Hopkins University to produce the trends, and we report the rates of cases, spikes of new cases, the number of days since the last reported case, and number of deaths. We also make adjustments to the assignments based on population so rural areas are not assigned trends based solely on case rates, which can be quite high relative to local populations.Two key factors are not consistently known or available and should be taken into consideration with the assigned trend. First is the amount of resources, e.g., hospital beds, physicians, etc.that are currently available in each area. Second is the number of recoveries, which are often not tested or reported. On the latter, we provide a probable number of active cases based on CDC guidance for the typical duration of mild to severe cases.Reasons for undertaking this work in March of 2020:The popular online maps and dashboards show counts of confirmed cases, deaths, and recoveries by country or administrative sub-region. Comparing the counts of one country to another can only provide a basis for comparison during the initial stages of the outbreak when counts were low and the number of local outbreaks in each country was low. By late March 2020, countries with small populations were being left out of the mainstream news because it was not easy to recognize they had high per capita rates of cases (Switzerland, Luxembourg, Iceland, etc.). Additionally, comparing countries that have had confirmed COVID-19 cases for high numbers of days to countries where the outbreak occurred recently is also a poor basis for comparison.The graphs of confirmed cases and daily increases in cases were fit into a standard size rectangle, though the Y-axis for one country had a maximum value of 50, and for another country 100,000, which potentially misled people interpreting the slope of the curve. Such misleading circumstances affected comparing large population countries to small population counties or countries with low numbers of cases to China which had a large count of cases in the early part of the outbreak. These challenges for interpreting and comparing these graphs represent work each reader must do based on their experience and ability. Thus, we felt it would be a service to attempt to automate the thought process experts would use when visually analyzing these graphs, particularly the most recent tail of the graph, and provide readers with an a resulting synthesis to characterize the state of the pandemic in that country, state, or county.The lack of reliable data for confirmed recoveries and therefore active cases. Merely subtracting deaths from total cases to arrive at this figure progressively loses accuracy after two weeks. The reason is 81% of cases recover after experiencing mild symptoms in 10 to 14 days. Severe cases are 14% and last 15-30 days (based on average days with symptoms of 11 when admitted to hospital plus 12 days median stay, and plus of one week to include a full range of severely affected people who recover). Critical cases are 5% and last 31-56 days. Sources:U.S. CDC. April 3, 2020 Interim Clinical Guidance for Management of Patients with Confirmed Coronavirus Disease (COVID-19). Accessed online. Initial older guidance was also obtained online. Additionally, many people who recover may not be tested, and many who are, may not be tracked due to privacy laws. Thus, the formula used to compute an estimate of active cases is: Active Cases = 100% of new cases in past 14 days + 19% from past 15-25 days + 5% from past 26-49 days - total deaths. On 3/17/2022, the U.S. calculation was adjusted to: Active Cases = 100% of new cases in past 14 days + 6% from past 15-25 days + 3% from past 26-49 days - total deaths. Sources: https://www.cdc.gov/mmwr/volumes/71/wr/mm7104e4.htm https://covid.cdc.gov/covid-data-tracker/#variant-proportions If a new variant arrives and appears to cause higher rates of serious cases, we will roll back this adjustment. We’ve never been inside a pandemic with the ability to learn of new cases as they are confirmed anywhere in the world. After reviewing epidemiological and pandemic scientific literature, three needs arose. We need to specify which portions of the pandemic lifecycle this map cover. The World Health Organization (WHO) specifies six phases. The source data for this map begins just after the beginning of Phase 5: human to human spread and encompasses Phase 6: pandemic phase. Phase six is only characterized in terms of pre- and post-peak. However, these two phases are after-the-fact analyses and cannot ascertained during the event. Instead, we describe (below) a series of five trends for Phase 6 of the COVID-19 pandemic.Choosing terms to describe the five trends was informed by the scientific literature, particularly the use of epidemic, which signifies uncontrolled spread. The five trends are: Emergent, Spreading, Epidemic, Controlled, and End Stage. Not every locale will experience all five, but all will experience at least three: emergent, controlled, and end stage.This layer presents the current trends for the COVID-19 pandemic by country (or appropriate level). There are five trends:Emergent: Early stages of outbreak. Spreading: Early stages and depending on an administrative area’s capacity, this may represent a manageable rate of spread. Epidemic: Uncontrolled spread. Controlled: Very low levels of new casesEnd Stage: No New cases These trends can be applied at several levels of administration: Local: Ex., City, District or County – a.k.a. Admin level 2State: Ex., State or Province – a.k.a. Admin level 1National: Country – a.k.a. Admin level 0Recommend that at least 100,000 persons be represented by a unit; granted this may not be possible, and then the case rate per 100,000 will become more important.Key Concepts and Basis for Methodology: 10 Total Cases minimum threshold: Empirically, there must be enough cases to constitute an outbreak. Ideally, this would be 5.0 per 100,000, but not every area has a population of 100,000 or more. Ten, or fewer, cases are also relatively less difficult to track and trace to sources. 21 Days of Cases minimum threshold: Empirically based on COVID-19 and would need to be adjusted for any other event. 21 days is also the minimum threshold for analyzing the “tail” of the new cases curve, providing seven cases as the basis for a likely trend (note that 21 days in the tail is preferred). This is the minimum needed to encompass the onset and duration of a normal case (5-7 days plus 10-14 days). Specifically, a median of 5.1 days incubation time, and 11.2 days for 97.5% of cases to incubate. This is also driven by pressure to understand trends and could easily be adjusted to 28 days. Source

  4. n

    USCounties cases

    • prep-response-portal.napsgfoundation.org
    Updated Apr 11, 2020
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    CivicImpactJHU (2020). USCounties cases [Dataset]. https://prep-response-portal.napsgfoundation.org/datasets/4cb598ae041348fb92270f102a6783cb
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    Dataset updated
    Apr 11, 2020
    Dataset authored and provided by
    CivicImpactJHU
    Area covered
    Description

    On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit the following sources:Global: World Health Organization (WHO)U.S.: U.S. Centers for Disease Control and Prevention (CDC)For more information, visit the Johns Hopkins Coronavirus Resource Center.This feature layer contains the most up-to-date COVID-19 cases for the US. Data is pulled from the Coronavirus COVID-19 Global Cases by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, the Red Cross, the Census American Community Survey, and the Bureau of Labor and Statistics, and aggregated at the US county level. This web map created and maintained by the Centers for Civic Impact at the Johns Hopkins University, and is supported by the Esri Living Atlas team and JHU Data Services. It is used in the COVID-19 United States Cases by County dashboard. For more information on Johns Hopkins University’s response to COVID-19, visit the Johns Hopkins Coronavirus Resource Center where our experts help to advance understanding of the virus, inform the public, and brief policymakers in order to guide a response, improve care, and save lives.

  5. l

    U.S. Counties and Territories for COVID-19 Trends

    • visionzero.geohub.lacity.org
    • disasterpartners.org
    Updated Apr 28, 2020
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    Urban Observatory by Esri (2020). U.S. Counties and Territories for COVID-19 Trends [Dataset]. https://visionzero.geohub.lacity.org/datasets/49c25e0ce50340e08fcfe51fe6f26d1e
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    Dataset updated
    Apr 28, 2020
    Dataset authored and provided by
    Urban Observatory by Esri
    Area covered
    Description

    On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit: U.S. Centers for Disease Control and Prevention (CDC)For more information, visit the Johns Hopkins Coronavirus Resource Center.Trends represent the day-to-day rate of new cases with a focus on the most recent 10 to 14 days. Includes Puerto Rico, Guam, Northern Marianas, and U.S. Virgin Islands. Daily new case counts are volatile for many reasons and sometimes the trends reflect that volatility. Thus, we decided to include longer-term summaries here. County Trends as of 9 Mar 20230 (-0) in Emergent1135 (+51) in Spreading1664 (-63) in Epidemic230 (+10) in Controlled110 (+2) in End StageNotes: Many states now only report once per week, and FL only once every two weeks. On 3/7/2022 we adjusted the formula for active cases to reflect the Omicron Variant which is documented to cause lower rates of serious and severe illness. To produce these trends we analyze daily updates from the Johns Hopkins University Coronavirus COVID-19 Global Cases Dashboard, though we expect to be one day behind the dashboard’s live feeds to allow for quality assurance of the data.For more information about COVID-19 trends, see our country level trends story map and the full methodology.Data Source: Johns Hopkins University CSSE US Cases by County dashboard and USAFacts for Utah County level Data.Feature layer generated from running the Join Features solution that is the basis for daily updates for the U.S. County COVID-19 Tends Story Map.

  6. US County and Territory COVID-19 Trend History

    • hub.scag.ca.gov
    Updated Jun 17, 2020
    + more versions
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    Urban Observatory by Esri (2020). US County and Territory COVID-19 Trend History [Dataset]. https://hub.scag.ca.gov/datasets/UrbanObservatory::us-county-and-territory-covid-19-trend-history
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    Dataset updated
    Jun 17, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    United States,
    Description

    On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit: U.S. Centers for Disease Control and Prevention (CDC)For more information, visit the Johns Hopkins Coronavirus Resource Center.This map is updated weekly. It shows COVID-19 Trend for the most recent Monday with a colored dot for each county. The larger the dot, the longer the county has had this trend. Includes Puerto Rico, Guam, Northern Marianas, U.S. Virgin Islands.Note: Nebraska Stopped reporting county level-results on 5/25/2021 and re-started on 9/26/21 with a lump-sum representing the previous four months - this impacted the weekly sum of cases fields.The intent of this map is to give more context than just the current day of new data because daily data for COVID-19 cases is volatile and can be unreliable on the day it is first reported. Weekly summaries in the counts of new cases smooth out this volatility.Click or tap on a county to see a history of trend changes and a weekly graph of new cases going back to February 1, 2020.For more information about COVID-19 trends, see the full methodology.Data Source: Johns Hopkins University CSSE US Cases by County dashboard.

  7. e

    Weekly Summary of U.S. COVID-19 Trends

    • coronavirus-resources.esri.com
    • coronavirus-disasterresponse.hub.arcgis.com
    Updated Jun 18, 2020
    + more versions
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    Urban Observatory by Esri (2020). Weekly Summary of U.S. COVID-19 Trends [Dataset]. https://coronavirus-resources.esri.com/maps/5490c0a73846465c821c647f0fd0435a
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    Dataset updated
    Jun 18, 2020
    Dataset authored and provided by
    Urban Observatory by Esri
    Area covered
    Description

    On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit: U.S. Centers for Disease Control and Prevention (CDC)For more information, visit the Johns Hopkins Coronavirus Resource Center.This map is updated weekly and currently shows data through March 5, 2023, which will be the final update of this map.Note: Nebraska stopped reporting county level-results on 5/25/2021 and re-started on 9/26/21 with a lump-sum representing the previous four months - this impacted the weekly sum of cases fields.It shows COVID-19 Trend for the most recent Monday with a colored dot for each county. The larger the dot, the longer the county has had this trend. Includes Puerto Rico, Guam, Northern Marianas, U.S. Virgin Islands.The intent of this map is to give more context than just the current day of new data because daily data for COVID-19 cases is volatile and can be unreliable on the day it is first reported. Weekly summaries in the counts of new cases smooth out this volatility. Click or tap on a county to see a history of trend changes and a weekly graph of new cases going back to February 8, 2020. This map is updated every Monday* based on data through the previous Sunday. See also this version of the map for another perspective.COVID-19 Trends show how each county is doing and are updated daily. We base the trend assignment on the number of new cases in the past two weeks and the number of active cases per 100,000 people. To learn the details for how trends are assigned, see the full methodology. There are five trends:Emergent - New cases for the first time or in counties that have had zero new cases for 60 or more days.Spreading - Low to moderate rates of new cases each day. Likely controlled by local policies and individuals taking measures such as wearing masks and curtailing unnecessary activities.Epidemic - Accelerating and uncontrolled rates of new cases.Controlled - Very low rates of new cases.End Stage - One or fewer new cases every 5 days in larger populations and fewer in rural areas.*Starting 8/22/2021 we began updating on Mondays instead of Tuesdays as a result of optimizing the scripts that produce the weekly analysis. For more information about COVID-19 trends, see the full methodology. Data Source: Johns Hopkins University CSSE US Cases by County dashboard and USAFacts for Utah County level Data.

  8. COVID-19 India

    • kaggle.com
    zip
    Updated Nov 4, 2025
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    Jami (2025). COVID-19 India [Dataset]. https://www.kaggle.com/mdahmadjami/covid19-india
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    zip(6255552 bytes)Available download formats
    Dataset updated
    Nov 4, 2025
    Authors
    Jami
    Area covered
    India
    Description

    About

    Community collected, cleaned and organized COVID-19 datasets about India sourced from different government websites which are freely available to all. Here we have digitized them, so it can be used by all the researchers and students.

    Infected Data

    Column Discription

    Main file in this dataset is COVID-19_India_Data.csv and the detailed descriptions are below.

    Date_reported : Date of the observation in YYYY-MM-DD
    cum_cases : Cumulative number of confirmed cases till that date
    cum_death : Cumulative number of deaths till that date
    cum_recovered : Cumulative number of recovered patients till that date
    new_recovered : Daily new recovery
    new_cases : New confirmed cases. Calculated by: current cum_cases - previous cum_case
    new_death : New confirmed deaths. Calculated by: current cum_death - previous cum_death
    cum_active_cases : Cumulative number of infected person till that date. Calculated by: cum_cases - cum_death - cum_recovered
    

    Vaccination data

    Column Discription

    Main file in this dataset is Vaccination.csv and the detailed descriptions are below.

    • date: date of the observation.
    • total_vaccinations: total number of doses administered. For vaccines that require multiple doses, each individual dose is counted. If a person receives one dose of the vaccine, this metric goes up by 1. If they receive a second dose, it goes up by 1 again. If they receive a third/booster dose, it goes up by again.
    • people_vaccinated: total number of people who received at least one vaccine dose. If a person receives the first dose of a 2-dose vaccine, this metric goes up by 1. If they receive the second dose, the metric stays the same.
    • people_fully_vaccinated: total number of people who received all doses prescribed by the vaccination protocol. If a person receives the first dose of a 2-dose vaccine, this metric stays the same. If they receive the second dose, the metric goes up by 1.
    • daily_vaccinations_raw: daily change in the total number of doses administered. It is only calculated for consecutive days. This is a raw measure provided for data checks and transparency, but we strongly recommend that any analysis on daily vaccination rates be conducted using daily_vaccinations instead.
    • daily_vaccinations: new doses administered per day (7-day smoothed). For countries that don't report data on a daily basis, we assume that doses changed equally on a daily basis over any periods in which no data was reported. This produces a complete series of daily figures, which is then averaged over a rolling 7-day window. An example of how we perform this calculation can be found here.
    • total_vaccinations_per_hundred: total_vaccinations per 100 people in the total population of the country.
    • people_vaccinated_per_hundred: people_vaccinated per 100 people in the total population of the country.

    Acknowledgements

  9. COVID-19 US Daily Data

    • kaggle.com
    zip
    Updated Sep 2, 2020
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    Altadata (2020). COVID-19 US Daily Data [Dataset]. https://www.kaggle.com/altadata/covid19us
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    zip(232018 bytes)Available download formats
    Dataset updated
    Sep 2, 2020
    Authors
    Altadata
    Area covered
    United States
    Description

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F5505749%2F2b83271d61e47e2523e10dc9c28e545c%2F600x200.jpg?generation=1599042483103679&alt=media" alt="">

    ALTADATA is a curated data marketplace where our subscribers and our data partners can easily exchange ready-to-analyze datasets and create insights with EPO, our visual data analytics platform.

    COVID-19 US Daily Data

    State level daily COVID-19 data for United States, provided by Johns Hopkins University (JHU) Center for Systems Science and Engineering (CSSE). If you want to use the updated version of the data, you can use our daily updated data with the help of api key by entering it via Altadata.

    Overview

    In this data product, you may find the latest and historical daily data on the COVID-19 pandemic for United States with the states level breakdown.

    The COVID‑19 pandemic, also known as the coronavirus pandemic, is an ongoing global pandemic of coronavirus disease 2019 (COVID‑19), caused by severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2). The outbreak was first identified in December 2019 in Wuhan, China. The World Health Organization declared the outbreak a Public Health Emergency of International Concern on 30 January 2020 and a pandemic on 11 March. As of 12 August 2020, more than 20.2 million cases of COVID‑19 have been reported in more than 188 countries and territories, resulting in more than 741,000 deaths; more than 12.5 million people have recovered.

    The Johns Hopkins Coronavirus Resource Center is a continuously updated source of COVID-19 data and expert guidance. They aggregate and analyze the best data available on COVID-19 - including cases, as well as testing, contact tracing and vaccine efforts - to help the public, policymakers and healthcare professionals worldwide respond to the pandemic.

    Methodology

    • Cases and Death counts include confirmed and probable (where reported)
    • Recovered cases are estimates based on local media reports, and state and local reporting when available, and therefore may be substantially lower than the true number. US state-level recovered cases are from COVID Tracking Project.
    • Active cases = total cases - total recovered - total deaths
    • Incidence Rate = cases per 100,000 persons
    • Case-Fatality Ratio (%) = Number recorded deaths / Number cases
    • US Testing Rate = total test results per 100,000 persons. The "total test results" are equal to "Total test results (Positive + Negative)" from COVID Tracking Project.
    • US Hospitalization Rate (%) = Total number hospitalized / Number cases. The "Total number hospitalized" is the "Hospitalized – Cumulative" count from COVID Tracking Project. The "hospitalization rate" and "Total number hospitalized" are only presented for those states which provide cumulative hospital data.
    • States Population data is retrieved from U.S. Census Bureau on top of the JHU CSSE's COVID-19 data

    Data Source

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    Data Dictionary

    • Reported Date (reported_date): Covid-19 Report Date
    • Province State (province_state): State name
    • Population (population): Estimated state populations as of July 2019, as per U.S. Census Bureau Population Division
    • Latitude (lat): Dot locations, not representative of a specific address
    • Longitude (lng): Dot locations longitude, not representative of a specific address
    • Confirmed Case (confirmed): Confirmed cases include presumptive positive cases and probable cases
    • Active cases (active): Active cases = total confirmed - total recovered - total deaths
    • Deaths (deaths): Death cases counts
    • Recovered (recovered): Recovered cases counts
    • Hospitalization Rate (hospitalization_rate): Total number of people hospitalized * 100...
  10. V

    Dataset from Systemic Allergic Reactions to SARS-CoV-2 Vaccination

    • data.niaid.nih.gov
    Updated Feb 6, 2025
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    ImmPort (a data-sharing platform funded by the National Institutes of Health); James R. Baker Jr., MD; Rebecca S. Gruchalla, MD, PhD; N. Franklin Atkinson Jr., MD (2025). Dataset from Systemic Allergic Reactions to SARS-CoV-2 Vaccination [Dataset]. http://doi.org/10.25934/PR00009442
    Explore at:
    Dataset updated
    Feb 6, 2025
    Dataset provided by
    Graduate Training Program in Clinical Investigation Associate TP Director, Allergy-Immunology Johns Hopkins Asthma & Allergy Center
    Mary H. Weiser Food Allergy Center and Michigan Nanotechnology Institute for Medicine and the Biological Sciences
    Division of Allergy and Immunology Departments of Internal Medicine and Pediatrics, University of Texas Southwestern
    Authors
    ImmPort (a data-sharing platform funded by the National Institutes of Health); James R. Baker Jr., MD; Rebecca S. Gruchalla, MD, PhD; N. Franklin Atkinson Jr., MD
    Area covered
    United States
    Variables measured
    Allergic Reaction
    Description

    Background: Allergic reactions have been reported to occur after vaccination with both the Pfizer-BioNTech COVID-19 Vaccine and Moderna COVID-19 Vaccine. Allergic reactions range from mild to severe and include life- threatening anaphylactic reactions, although no deaths have been reported with either vaccine.

    This study is designed with two principal aims:

    • To estimate the proportions of systemic allergic reactions to the Pfizer-BioNTech COVID-19 Vaccine and the Moderna COVID-19 Vaccine in a High-Allergy/Mast Cell Disorder (HA/MCD) population, and

    • If the risk in the HA/MCD is demonstrable, to determine whether the proportions are higher in the HA/MCD in comparison to a representative population without severe allergies or mast cell disorders

  11. COVID 19 DATASET TILL 22/2/2022

    • kaggle.com
    zip
    Updated Feb 23, 2022
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    Taranveer Singh Anttal (2022). COVID 19 DATASET TILL 22/2/2022 [Dataset]. https://www.kaggle.com/datasets/taranvee/covid-19-dataset-till-2222022
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    zip(9372578 bytes)Available download formats
    Dataset updated
    Feb 23, 2022
    Authors
    Taranveer Singh Anttal
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Data on COVID-19 (coronavirus) by Our World in Data

    🗂️ Download our complete COVID-19 dataset : CSV | XLSX | JSON

    Our complete COVID-19 dataset is a collection of the COVID-19 data maintained by Our World in Data. We will update it daily throughout the duration of the COVID-19 pandemic (more information on our updating process and schedule here). It includes the following data:

    MetricsSourceUpdatedCountries
    VaccinationsOfficial data collated by the Our World in Data teamDaily218
    Tests & positivityOfficial data collated by the Our World in Data teamWeekly151
    Hospital & ICUOfficial data collated by the Our World in Data teamDaily47
    Confirmed casesJHU CSSE COVID-19 DataDaily216
    Confirmed deathsJHU CSSE COVID-19 DataDaily216
    Reproduction rateArroyo-Marioli F, Bullano F, Kucinskas S, Rondón-Moreno CDaily189
    Policy responsesOxford COVID-19 Government Response TrackerDaily186
    Other variables of interestInternational organizations (UN, World Bank, OECD, IHME…)Fixed241

    A specific section of this repository is also dedicated to vaccinations, with a lighter dataset containing only vaccination data.

    The data you find here and our data sources

    • Confirmed cases and deaths: our data comes from the COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). We discuss how and when JHU collects and publishes this data here. The cases & deaths dataset is updated daily. *Note: the number of cases or deaths reported by any institution—including JHU, the WHO, the ECDC and others—on a given day does not necessarily represent the actual number on that date. This is because of the long reporting chain that exists between a new case/death and its inclusion in statistics. This also means that negative values in cases and deaths can sometimes appear when a country corrects historical data, because it had previously overestimated the number of cases/deaths. Alternatively, large changes can sometimes (although rarely) be made to a country's entire time series if JHU decides (and has access to the necessary data) to correct values retrospectively.*
    • Hospitalizations and intensive care unit (ICU) admissions: our data is collected from official sources and collated by Our World in Data. The complete list of country-by-country sources is available here.
    • Testing for COVID-19: this data is collected by the Our World in Data team from official reports; you can find further details in our post on COVID-19 testing, including our checklist of questions to understand testing data, information on geographical and temporal coverage, and detailed country-by-country source information. The testing dataset is updated around twice a week.
    • Vaccinations against COVID-19: this data is collected by the Our World in Data team from official reports.
    • Other variables: this data is collected from a variety of sources (United Nations, World Bank, Global Burden of Disease, Blavatnik School of Government, etc.). More information is available in our codebook.

    The complete Our World in Data COVID-19 dataset

    **Our complete COVID-19 dataset is available in CSV, XLSX, and JSON formats, and inc...

  12. c

    The Meningococcal Vaccines Market will grow at a CAGR of 11.4% from 2023 to...

    • cognitivemarketresearch.com
    pdf,excel,csv,ppt
    Updated Aug 12, 2025
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    Cognitive Market Research (2025). The Meningococcal Vaccines Market will grow at a CAGR of 11.4% from 2023 to 2030! [Dataset]. https://www.cognitivemarketresearch.com/meningococcal-vaccines-market-report
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Aug 12, 2025
    Dataset authored and provided by
    Cognitive Market Research
    License

    https://www.cognitivemarketresearch.com/privacy-policyhttps://www.cognitivemarketresearch.com/privacy-policy

    Time period covered
    2021 - 2033
    Area covered
    Global
    Description

    The Meningococcal Vaccines market size is valued at US$ 5.2 billion in 2022 and is projected to reach US$ 13.1 billion till 2030 with a CAGR of 11.4% during forecast period. Factors Affecting Meningococcal Vaccines Market Growth

    Growing Incidence of Meningitis:
    

    The global market for meningitis vaccines is expected to expand as a result of an increase in the prevalence of meningitis and the need for meningitis vaccinations. For instance, according to data from the academic publishing organization Elsevier Inc., based in the Netherlands, more than 25 million cases and 236,000 deaths due to meningitis were reported worldwide in 2019. Meningitis is caused by certain bacteria, viruses and fungi, and parasites, and it can be transmitted from person to person. Therefore, the prevalence of meningitis is increasing, due to which the meningococcal vaccine demand is increasing.

    Increasing Government Initiative:
    

    The global meningitis vaccine market is anticipated to increase over the projected period as a result of increasing measures taken by regulatory bodies and national governments to tackle the increasing occurrence of meningitis. For instance, the world health organization and its partners introduced the first-ever worldwide strategy to eradicate meningitis by 2030 in September 2021. The policy aims to eradicate bacterial meningitis epidemics, reduce deaths by 70%, and cut the number of cases by half by 2030.

    The Restraining Factor of Meningococcal Vaccines:

    High Cost of Vaccination
    

    The high cost of meningitis vaccinations is the main factor that will probably hinder the growth of the worldwide market for meningitis vaccines. For instance, experts from Johns Hopkins University determined that it would not be cost-effective to require meningitis B vaccination for all college students in 2018. The universal vaccination against meningitis B or meningococcal disease serogroup B, for college-aged students, would only be advantageous if the vaccine cost less than US$ 65, according to research. It cost an average of US$ 324.

    Opportunities on Meningococcal Vaccines:

    Growing Research & Development:
    

    The development of the market is estimated to be fuelled by the numerous vaccines and phase 1 vaccination research projects that are expected to become commercially available during the forecast period. To compare the safety, immunogenicity, and tolerability of pentavalent meningococcal vaccine candidate PF-06886992 with licensed meningococcal vaccines in adolescents and young adults, Pfizer, began phase 1 clinical studies of the drug in June 2020. Furthermore, a phase 2 clinical trial for the conjugate vaccine Menactra, produced by Serum Institute of India, is now underway as a result, the market is expanding owing to all these trials.

    Growing Government Initiative: 
    

    During the projected period, expanding activities by the government and other regulatory bodies are anticipated to fuel the market. For instance, the first-ever worldwide strategy to combat meningitis, a worldwide roadmap to eradicate meningitis by 2030, was introduced by WHO and its partners in September 2021. The major goal is to end bacterial meningitis epidemics, cut mortality by 70% and eliminate new cases by 2030.

    Impact of the COVID-19 Pandemic on the Meningococcal Vaccines Market:

    The covid-19 has had a negative impact on the market. Due to a decline in meningitis vaccination rates, the Covid pandemic had a detrimental economic effect on the world market for meningitis vaccinations. For instance, Elsevier BV, a Dutch academic publishing house with a focus on scientific, technical, and medical material reported in an article published eleven states of Brazil. The covid-19 pandemic consequently had a negative effect on the number of meningitis vaccination doses delivered. Consequently, the covid-19 had a detrimental economic effect on the market for meningitis vaccines because of drop-in immunization rates. Introduction of Meningococcal Vaccines

    Neisseria meningitidis, a bacterium, is the source of the uncommon, severe condition known as meningococcal disease. It can result in blood infection as well as meningitis, an infection of the brain and spinal cord. Any vaccination used to stop Neisseria meningitides infection is referred to as a meningococcal vaccine, the following meningococcal strains: A, B, C, W-135, and Y. Different versions are effective again...

  13. a

    Coronavirus COVID-19 Cases

    • coronavirus-disasterresponse.hub.arcgis.com
    • coronavirus-resources.esri.com
    • +2more
    Updated Feb 6, 2020
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    CSSE_covid19 (2020). Coronavirus COVID-19 Cases [Dataset]. https://coronavirus-disasterresponse.hub.arcgis.com/maps/bbb2e4f589ba40d692fab712ae37b9ac
    Explore at:
    Dataset updated
    Feb 6, 2020
    Dataset authored and provided by
    CSSE_covid19
    Area covered
    Description

    On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit the following sources:Global: World Health Organization (WHO)U.S.: U.S. Centers for Disease Control and Prevention (CDC)For more information, visit the Johns Hopkins Coronavirus Resource Center.This feature layer contains the most up-to-date COVID-19 cases and the latest trend plot. It covers the US (county or state level), China, Canada, Australia (province/state level), and the rest of the world (country/region level, represented by either the country centroids or their capitals). Data sources are WHO, CDC, ECDC, NHC, DXY, 1point3acres, Worldometers.info, BNO, the COVID Tracking Project (testing and hospitalizations), state and national government health departments, and local media reports. This layer is created and maintained by the Center for Systems Science and Engineering (CSSE) at the Johns Hopkins University. This feature layer is supported by Esri Living Atlas team, JHU APL and JHU Data Services. This layer is opened to the public and free to share. Contact us.

  14. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Statista (2022). COVID-19 cases and deaths per million in 210 countries as of July 13, 2022 [Dataset]. https://www.statista.com/statistics/1104709/coronavirus-deaths-worldwide-per-million-inhabitants/
Organization logo

COVID-19 cases and deaths per million in 210 countries as of July 13, 2022

Explore at:
163 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jul 13, 2022
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Worldwide
Description

Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

The difficulties of death figures

This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

Where are these numbers coming from?

The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

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